Tech Forecasts: what is the next big thing in 2019?

It is the time of the year when consultants and analysts take stock of the technology trends and prognosticate over emerging technologies. There are many variances to the forecasts and the number of trends predicted, ranging from “top 5” to “top 20” and in-between*. The predictions are around flavors of digital tools and technologies - AI/ML, big-data, SMAC, analytics, Big Data and a few BHAGS like autonomous vehicles and commercial space travel.

Having spent the past couple of decades in the vibrant global tech world, I continue to study and reflect on these forecasts. When read collectively, they are a barometer of where the business investments are headed, especially since the major trends seem to converge on a few common themes. It is also obvious that most analysts glance at the short-term rear-view to ‘predict’ what they see bubbling to the top.

Corporate Digitization playing catchup with Consumer Tech

In the past few years most of the promising emerging technologies were adopted by consumers before finding their way into the corporate world. The earlier generation of iPhones set the bar high for smartphones and consumer adoption eventually leading to BYOD in enterprises. Similarly, consumers began to experience ubiquitous access to WiFi and corporate IT began to follow suite. Machine Learning enabled Chatbots and digital assistants are re-defining consumer User Interfaces using voice and Natural Language to interact with systems.

Many of these technologies are being designed into application platforms and products, enabling corporate users. It is likely that in 2019, we will encounter “2.0” of many of the trends that have already been firming up this year. Let me illustrate with a couple of technology trends that are common in analyst reports

• Blockchain – Even with the wild swing in the market for Bitcoins this year, tech watchers continued to keep the focus squarely on the underlying cryptographic techniques. Blockchain adoption has moved beyond pilot to production in several industry verticals. Adopting Blockchain techniques to enable trust and traceability between corporate entities will transform some segments of the industry; but it is primarily an underlying technology plumbing to enable Enterprise Architectures, and will be transparent to most users. This is because even the most innovative techniques in data and integration are primarily about enabling secure data transfer. 
• Robotics and Automation – I spent the good part of this year strategizing and operationalizing Robotic Process Automation (RPA) for a Fortune-500 company. These Intelligent Automation techniques continue to make inroads without waiting for organizations to transform their business processes. The reason for this is rather straightforward: even as we move into 2019, there are too many gaps in legacy platforms and processes, that are either too expensive to transform or replace. This is the sweet spot that where adoption of intelligent Automation will continue to make inroads.
• Machine Learning and Cognitive Computing – Chatbots and intelligent assistants are appearing in a variety of internal and external facing corporate scenarios. However, these are just a small subset of use-cases. Most software vendors are beginning to embed AI and ML techniques into their technology platforms that include supply-chain and planning, recruitment, talent sourcing, big data and analytics, financial data processing and within ERP and CRM systems among others. Such adoption of AI and ML, while transparent to corporate business and technology teams are transforming usability of systems and productivity of users. 

So what do the technology forecasts mean to us?

The year-end is certainly the time to reflect on changes personal and professional, but technology trends and innovations do not follow any calendar; especially not the Gregorian calendar.

• ‘Technology innovation’ is really a continuum of change that we need to be embracing 
• Depending on the nature of your role in an organization and its business, there are some technologies that will influence you and your business more than others will. 
• Your businesses’ appetite for change will dictate the pace of adoption in your organization

A link to a small sampling of tech forecasts - Gartner Top 10 Strategic Technology Trends for 2019 || Deloitte's 2019 Technology Industry Outlook || ZDNet What’s next for 2019? IoT trends and predictions || Inc. 31 Tech Predictions for 2019 || Looking in a rear-view - Top 10 technology trends to watch in 2018

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Thanks for reading! Please click on Like, or Share, Tweet and Comment below to continue this conversation or share your favorite 'trend to watch' | Reposted from my LinkedIn Blog

Indian Roads: the final frontier for Autonomous and Self-Driving Cars

I happen to be among a rare breed of NRI/PIOs who are as comfortable driving in Anytown USA as they are on busy and chaotic Bangalore roads. This said, it takes a few days of ‘acclimatization’ riding on Olas, Uber and Auto Rickshaws before I gain confidence to get behind the wheels. During my current stint in Bangalore, while driving a small Maruti car, I have been musing on former Uber CEO Travis Kalanick’s statement that “India will be the last place to get autonomous cars.”

When Kalanick made this proclamation a few months ago, it raised a few eyebrows among the digirati, and proponents of Autonomous vehicles and AI.

The technologies behind autonomous cars are advancing at a fast pace. Billions of dollars are being poured into it by Automakers and rideshare companies. Almost every day we see news of ‘yet another’ innovation in self-steering, LIDAR, GPS, Digital Maps and related technologies including AI and robotics. (link to a couple of recent deals) Some of these ideas and technologies sound futuristic and SCI-FIish, though many of these technologies are beginning to appear in high-end automobiles.

After driving on Bangalore roads for the past few months, I will have to concur with Kalanick’s proclamation. And here are 10 reasons why Bangalore roads will be the last place on earth to get autonomous cars:



#1. Right of way? When it comes to use of roads, everything and everyone has a right of way, Including pedestrians and cows. Drivers may swear at cyclists, pedestrians or even guys riding horses ziz-zagging through traffic, but shrug it off as par for the course. Apparently the guy riding a horse has as much right to be on the road as my Maruti.
Implication for designers of autonomous cars: Any self-driving technology will have to accommodate for erratic and unpredictable presence of vehicles and non-vehicles on roads that claim an equal right-of-way.



#2. Might is right – Paraphrasing George Orwell, when it comes to Indian roads, all vehicles are equal, but some vehicles are more equal than others. Bangalore traffic follows an informal pecking order with Public buses at the top of the food chain, followed by ‘G’ plated government and police vehicles, followed by larger SUVs, yellow-plated commercial vehicles and so on. Of course, Autorickshaws and bikes seem to have a license to ziz-zag as they please.
Implication: My description of the informal pecking order is merely an empirical observation. Good luck to analysts trying to decipher and codify the complex Orwell pecking order on Indian roads!

#3. Eye-contact – At busy intersections where traffic begins to crawl, pedestrians, bike-riders and others will try to make eye-contact, wave or make other gestures to indicate their intent
Implication: There is obviously a lot more than meets the eye. LIDAR, Digital sensors and cameras will have to be smart enough to speedily decipher such human cues from a distance.

#4. Horn-OK-Please – Trucks and busses on highways routinely have “horn please” painted behind to remind drivers that honking is not only expected but a normal mode of communication. Honking on Indian roads takes an art-form and is not a precise science. Honking can range from benign expression of impatience and a subtle warning to pedestrians and bikers to more serious expression of rage.
Implication: Making sense of a honk requires contextualized interpretation: Try deciphering a single horn, and what it’s trying to communicate from among a cacophony of honks in a busy street.


#5. Streets with potholes, dug up and after monsoons, waterlogged. After the recent rains, unfortunate bikers and scooters in Bangalore trying to avoid new potholes have skid, and been fatally hit by oncoming traffic.
Implication: The challenge is not just about potholes but the unpredictability it induces, requiring split-second reflexes among motorists. LIDAR, DGPS and Digital maps may not be able to predict the next roadblock, pothole or dug-up road.

#6. Dealing with fender-benders – Driving on congested roads with bumper-to-bumper traffic will inevitably lead to fender-benders, or worse. Crowds of gawkers instantly gather around traffic accidents while some mobs are known to vent their 'fury' on helpless drivers.
Implication: One can only guess what happens when a self-driven car meets with an accident. Is it going to call on its AI driven digital assistant, and wait for the police while the other motorist invokes the mob to act?


#7. Dealing with traffic-cops –These men (and women) in uniform try hard to bring a bit of order in chaotic, overcrowded roads. Motorists flagged down by traffic-cops are generally expected to pay a ‘spot fine’ and try to ‘negotiate’ down the fine or plead their case.
Implication: What happens when a self-driven car is flagged down for a traffic violation? Does it to call its digital assistant to help with the ‘negotiation’ or just pay the fine and take the ticket? The social implications here are unclear.

#8. There are rules and then there are un-codified mores. Transport authorities have defined basic rules like ‘driving on the left side of the road,’ ‘overtaking from the right’ etc which motorists are expected to learn before getting a driver’s license. In addition, there are un-codified mores like the art of slowing at intersections and inching forward without stopping and yielding.
Implication: Obvious challenge of designing a system to decipher and work with ever changing, un-codified mores

#9. Driving towards landmarks: Directions from point-A to point-B in major localities are easy enough. It gets trickier when the destination happens to be in a small, narrow by-lanes. Even though I have my coordinates geo-tagged in Ola and Uber, the drivers invariably call to ask for a nearby ‘landmark’ that includes a dental clinic, liquor shop behind the house or the hardware-shop on the 80-feet road.
Implication: GPS and Digital Maps will need a tremendous amount of intelligence (AI ?) to identify and recognize small and large landmarks as humans understand them.

#10. Human Behavior – People in India have been learning to adapt to an increasing number of cars and automobiles on existing narrow roads and lanes. Even in a span of the past 10 years, one can see a remarkable reduction in the number of bicycles on roads and narrow roads morphing into parking spots with hardly any space left for motors to navigate.
Implication: Even the best designed system will have to continually keep up with changing human behavior, and surging population trying to adapt to the constraints.

Some of these observations may sound tongue and cheek, and can certainly be addressed with the right technologies and system design. Even in Bangalore, one might begin seeing autonomous vehicles in ‘controlled traffic’ environments in University, Defense, Governmental and Corporate campuses as the Infosys’ proof-of-concept in their campus highlights.

Perhaps the futurists eyeing the Indian market should step back from self-driving car hype, and focus on an unmet need: a relatively inexpensive electric car that can ‘idle’ smog-free in congested traffic! Wonder what will get Elon Musk to rethink his decision of bringing Teslas to India?
Thanks for reading! Please click on Like, Share, Tweet and Comment below to continue this conversation | Reposted from Linkedin Pulse | [Images in the writeup are googled stock pictures]